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  • Multiple sequence alignment of homologous cytochrome C protein sequences using Jalview viewer.

    Sequence Similarity: An inquiry based and "under the hood" approach for incorporating molecular sequence...

    Learning Objectives
    At the end of this lesson, students will be able to:
    • Define similarity in a non-biological and biological sense when provided with two strings of letters.
    • Quantify the similarity between two gene/protein sequences.
    • Explain how a substitution matrix is used to quantify similarity.
    • Calculate amino acid similarity scores using a scoring matrix.
    • Demonstrate how to access genomic data (e.g., from NCBI nucleotide and protein databases).
    • Demonstrate how to use bioinformatics tools to analyze genomic data (e.g., BLASTP), explain a simplified BLAST search algorithm including how similarity is used to perform a BLAST search, and how to evaluate the results of a BLAST search.
    • Create a nearest-neighbor distance matrix.
    • Create a multiple sequence alignment using a nearest-neighbor distance matrix and a phylogram based on similarity of amino acid sequences.
    • Use appropriate bioinformatics sequence alignment tools to investigate a biological question.
  • Reprinted by permission from Macmillan Publishers Ltd.

    A Hands-on Introduction to Hidden Markov Models

    Learning Objectives
    • Students will be able to process unannotated genomic data using ab initio gene finders as well as other inputs.
    • Students will be able to defend the proposed gene annotation.
    • Students will reflect on the other uses for HMMs.
  • Grow the Gradient game board. A student moves game pieces on the game board as they learn how the loop of Henle creates a salt concentration gradient in the medulla.

    Grow the Gradient: An interactive countercurrent multiplier game

    Learning Objectives
    • Students will be able to simulate the movement of water and sodium at each region of the loop of Henle.
    • Students will be able to associate osmosis and active transport with movement of water/solutes at each region of the loop of Henle.
    • Students will be able to model how the descending and ascending limbs of the loop of Henle maintain a concentration gradient within the medulla.
    • Students will be able to predict the effects of altering normal water and salt movement out of the loop of Henle on the salt concentration of the medulla, urine concentration, and urine volume.
    Advanced Learning Objectives for Extensions
    • Students will be able to predict the impact of the length of the loop of Henle on the magnitude of the concentration gradient within the medulla.
    • Students will be able to predict the length of the loop of Henle in organisms from different habitats.
  • Students using the Understanding Eukaryotic Genes curriculum to construct a gene model. Students are working as a pair to complete each Module using classroom computers.

    An undergraduate bioinformatics curriculum that teaches eukaryotic gene structure

    Learning Objectives
    Module 1
    • Demonstrate basic skills in using the UCSC Genome Browser to navigate to a genomic region and to control the display settings for different evidence tracks.
    • Explain the relationships among DNA, pre-mRNA, mRNA, and protein.
    Module 2
    • Describe how a primary transcript (pre-mRNA) can be synthesized using a DNA molecule as the template.
    • Explain the importance of the 5' and 3' regions of the gene for initiation and termination of transcription by RNA polymerase II.
    • Identify the beginning and the end of a transcript using the capabilities of the genome browser.
    Module 3
    • Explain how the primary transcript generated by RNA polymerase II is processed to become a mature mRNA, using the sequence signals identified in Module 2.
    • Use the genome browser to analyze the relationships among:
    • pre-mRNA
    • 5' capping
    • 3' polyadenylation
    • splicing
    • mRNA
    Module 4
    • Identify splice donor and acceptor sites that are best supported by RNA-Seq data and TopHat splice junction predictions.
    • Utilize the canonical splice donor and splice acceptor sequences to identify intron-exon boundaries.
    Module 5
    • Determine the codons for specific amino acids and identify reading frames by examining the Base Position track in the genome browser.
    • Assemble exons to maintain the open reading frame (ORF) for a given gene.
    • Define the phases of the splice donor and acceptor sites and describe how they impact the maintenance of the ORF.
    • Identify the start and stop codons of an assembled ORF.
    Module 6
    • Demonstrate how alternative splicing of a gene can lead to different mRNAs.
    • Show how alternative splicing can lead to the production of different polypeptides and result in drastic changes in phenotype.
  • 3D Print Models: A collection of 3D models printed from online repository files.
  • Modeling the Research Process: Authentic human physiology research in a large non-majors course

    Learning Objectives
    Students will be able to:
    • Read current scientific literature
    • Formulate testable hypotheses
    • Design an experimental procedure to test their hypothesis
    • Make scientific observations
    • Analyze and interpret data
    • Communicate results visually and orally
  • MA plot of RNA-seq data. An MA plot is a visual summary of gene expression data which identifies genes showing differential expression between two treatments.

    Tackling "Big Data" with Biology Undergrads: A Simple RNA-seq Data Analysis Tutorial Using Galaxy

    Learning Objectives
    • Students will locate and download high-throughput sequence data and genome annotation files from publically available data repositories.
    • Students will use Galaxy to create an automated computational workflow that performs sequence quality assessment, trimming, and mapping of RNA-seq data.
    • Students will analyze and interpret the outputs of RNA-seq analysis programs.
    • Students will identify a group of genes that is differentially expressed between treatment and control samples, and interpret the biological significance of this list of differentially expressed genes.
  • Model skeleton

    Plotting Cranial and Spinal Nerve Pathways in a Human Anatomy Lab

    Learning Objectives
    • Identify and describe the functions of cranial and spinal nerves
    • Identify cranial and spinal nerve origination points and what structures they innervate
    • Trace the routes that cranial and spinal nerves take throughout the body
  • Abelson kinase signaling network. The image shows many connections between genes and illustrates that signaling molecules and pathways function within networks. It emphasizes the indispensability of computational tools in understanding the molecular functioning of cells. The image was generated with Cytoscape from publicly accessible protein-protein interactions databases.

    Investigating Cell Signaling with Gene Expression Datasets

    Learning Objectives
    Students will be able to:
    • Explain the hierarchical organization of signal transduction pathways.
    • Explain the role of enzymes in signal propagation and amplification.
    • Recognize the centrality of signaling pathways in cellular processes, such as metabolism, cell division, or cell motility.
    • Rationalize the etiologic basis of disease in terms of deranged signaling pathways.
    • Use software to analyze and interpret gene expression data.
    • Use an appropriate statistical method for hypotheses testing.
    • Produce reports that are written in scientific style.
  • Using the Cell Engineer/Detective Approach to Explore Cell Structure and Function

    Learning Objectives
    Students will be able to:
    • Identify the major cell organelles
    • List the major functions of the organelles
    • Predict how changes in organelle/cell structure could alter cellular function
    • Explain how overall cellular function is dependent upon organelles/cell structure
    • Relate cell structure to everyday contexts
  • Normal Arabidopsis plants (A) have flat, spatula shaped leaves. asymmetric leaves2 (as2) mutant plants (B) have leaves that are curled under and slightly twisted. asymmetric leaves1(as1) mutant plants (C) have leaves that are curled under and twisted but also have reduced petioles.  In the laboratory activities I present, students analyze the sequence of the as1 and as2 alleles and computationally model the wild-type and mutant proteins. Visualizing the 3-D structure of the proteins helps students understan

    Using computational molecular modeling software to demonstrate how DNA mutations cause phenotypes

    Learning Objectives
    Students successfully completing this lesson will:
    1. Practice basic molecular biology laboratory skills such as DNA isolation, PCR, and gel electrophoresis.
    2. Gather and analyze quantitative and qualitative scientific data and present it in figures.
    3. Use bioinformatics to analyze DNA sequences and obtain protein sequences for molecular modeling.
    4. Make and analyze three-dimensional (3-D) protein models using molecular modeling software.
    5. Write a laboratory report using the collected data to explain how mutations in the DNA cause changes in protein structure/function which lead to mutant phenotypes.